Method and system for evaluating quality assurance criteria in delivery of a treatment plan

ABSTRACT

System and method of determining whether a component of a radiation therapy system is operating within a dosimetric tolerance. The method can include the acts of generating a treatment plan for a patient, the treatment plan specifying a radiation amount to be delivered to the patient, delivering radiation to the patient according to the treatment plan, obtaining feedback during the delivery of radiation, the feedback related to one of a position, a velocity, and an acceleration for one of a multi-leaf collimator, a gantry, a couch, and a jaws, generating a mathematical model based on the feedback for one of the multi-leaf collimator, the gantry, the couch, and the jaws, calculating a delivered dose amount based on the mathematical model and treatment plan information, calculating a deviation in dose between the radiation amount specified in the treatment plan and the delivered dose amount, and determining whether the deviation in dose is within a dosimetric tolerance for the one of the multi-leaf collimator, the gantry, the couch, and the jaws.

RELATED APPLICATIONS

This application is a continuation-in-part of and claims priority toU.S. patent application Ser. No. 11/459,152, filed on Jul. 21, 2006,which is a non-provisional of and claims priority to U.S. ProvisionalPatent Application No. 60/701,580, filed on Jul. 22, 2005, titled SYSTEMAND METHOD FOR FEEDBACK GUIDED QUALITY ASSURANCE AND ADAPTATIONS TORADIATION THERAPY TREATMENT. The entire contents of these applicationare incorporated herein by reference.

BACKGROUND OF THE INVENTION

Over the past decades improvements in computers and networking,radiation therapy treatment planning software, and medical imagingmodalities (CT, MRI, US, and PET) have been incorporated into radiationtherapy practice. These improvements have led to the development ofimage guided radiation therapy (“IGRT”). IGRT is radiation therapy thatuses cross-sectional images of the patient's internal anatomy to bettertarget the radiation dose in the tumor while reducing the radiationexposure to healthy organs. The radiation dose delivered to the tumor iscontrolled with intensity modulated radiation therapy (“IMRT”), whichinvolves changing the size, shape, and intensity of the radiation beamto conform to the size, shape, and location of the patient's tumor. IGRTand IMRT lead to improved control of the tumor while simultaneouslyreducing the potential for acute side effects due to irradiation ofhealthy tissue surrounding the tumor.

IMRT is becoming the standard of care in several countries. However, inmany situations, IMRT is not used to treat a patient due to time,resources, and billing constraints. Daily images of the patient can beused to guarantee that the high gradients generated by IMRT plans arelocated on the correct position for patient treatment. Also these imagescan provide necessary information to adapt the plan online or offline ifneeded.

It is commonly known in the field of radiation therapy that there aremany sources of uncertainty and change that can occur during a course ofa patient's treatment. Some of these sources represent random errors,such as small differences in a patient's setup position each day. Othersources are attributable to physiological changes, which might occur ifa patient's tumor regresses or the patient loses weight during therapy.A third possible category regards motion. Motion can potentially overlapwith either of the other categories, as some motion might be more randomand unpredictable, such as a patient coughing or passing gas, whereasother motion can be more regular, such as breathing motion, sometimes.

SUMMARY OF THE INVENTION

In radiation therapy, uncertainties can affect the quality of apatient's treatment. For example, when delivering a treatment dose to atarget region, it is standard practice to also treat a high-dose“margin” region about the target. This helps ensure that the targetreceives the desired dose, even if its location changes during thecourse of the treatment, or even during a single fraction. The lessdefinite a target's location, the larger the margins that typically needto be used.

Adaptive radiation therapy generally refers to the concept of usingfeedback during the course of radiation therapy treatment to improvefuture treatments. Feedback can be used in off-line adaptive therapyprocesses and on-line adaptive therapy processes. Off-line adaptivetherapy processes occur while the patient is not being treated, such asin between treatment fractions. In one version of this, during eachfraction, a new CT image of the patient is acquired before or after eachof the fractions. After the images are acquired from the first fewtreatment fractions, the images are evaluated to determine an effectiveenvelope of the multi-day locations of target structures. A new plan canthen be developed to better reflect the range of motion of the targetstructure, rather than using canonical assumptions of motion. A morecomplex version of off-line adaptive therapy is to recalculate thedelivered dose after each fraction and accumulate these doses,potentially utilizing deformation techniques, during this accumulationto account for internal motion. The accumulated dose can then becompared to the planned dose, and if any discrepancies are noted,subsequent fractions can be modified to account for the changes.

On-line adaptive therapy processes typically occur while the patient isin the treatment room, and potentially, but not necessarily, during atreatment delivery. For example, some radiation therapy treatmentsystems are equipped with imaging systems, such as on-line CT or x-raysystems. These systems can be used prior to treatment to validate oradjust the patient's setup for the treatment delivery. The imagingsystems may also be used to adapt the treatment during the actualtreatment delivery. For example, an imaging system potentially can beused concurrently with treatment to modify the treatment delivery toreflect changes in patient anatomy.

One aspect of the present invention is to disclose new opportunities forthe application of adaptive therapy techniques, and additional aspectsare to present novel methods for adaptive therapy. In particular,adaptive therapy has typically focused on feedback to modify a patient'streatment, but the present invention focuses on adaptive therapyprocesses being used in a quality assurance context. This isparticularly true in the context of whole-system verification.

For example, a detector can be used to collect information indicatinghow much treatment beam has passed through the patient, from which themagnitude of the treatment output can be determined as well as anyradiation pattern that was used for the delivery. The benefit of thisdelivery verification process is that it enables the operator to detecterrors in the machine delivery, such as an incorrect leaf pattern ormachine output.

However, validating that the machine is functioning properly does notitself ensure proper delivery of a treatment plan, as one also needs tovalidate that the external inputs used to program the machine areeffective and consistent. Thus, one aspect of the invention includes thebroader concept of an adaptive-type feedback loop for improved qualityassurance of the entire treatment process. In this aspect, the inventionincludes the steps of positioning the patient for treatment and using amethod for image-guidance to determine the patient's position,repositioning the patient as necessary for treatment based upon theimage-guidance, and beginning treatment. Then, either during or aftertreatment, recalculating the patient dose and incorporating the patientimage information that had been collected before or during treatment.After completion of these steps, quality assurance data is collected toanalyze the extent to which the delivery was not only performed asplanned, but to validate that the planned delivery is reasonable in thecontext of the newly available data. In this regard, the concept offeedback is no longer being used to indicate changes to the treatmentbased on changes in the patient or delivery, but to validate theoriginal delivery itself.

As an example, it is possible that a treatment plan might be developedfor a patient, but that the image used for planning became corrupted,such as by applying an incorrect density calibration. In this case, thetreatment plan will be based upon incorrect information, and might notdeliver the correct dose to the patient. Yet, many quality assurancetechniques will not detect this error because they will verify that themachine is operating as instructed, rather than checking whether theinstructions to the machine are based on correct input information.Likewise, some adaptive therapy techniques could be applied to thisdelivery, but if the calibration problem of this example persisted, thenthe adapted treatments would suffer from similar flaws.

There are a number of processes that can be used to expand the use offeedback for quality assurance purposes. For example, in one embodiment,this process would include the delivery verification techniquesdescribed above. The validation of machine performance that thesemethods provide is a valuable component of a total-system qualityassurance toolset. Moreover, the delivery verification processes can beexpanded to analyze other system errors, such as deliveries based onimages with a truncated field-of-view.

In one embodiment, the invention provides a method of determiningwhether a component of a radiation therapy system is operating within adosimetric tolerance. The method comprises generating a treatment planfor a patient, the treatment plan specifying a radiation amount to bedelivered to the patient, delivering radiation to the patient accordingto the treatment plan, obtaining feedback during the delivery ofradiation, the feedback related to one of a position, a velocity, and anacceleration for one of a multi-leaf collimator, a gantry, a couch, anda jaws, generating a mathematical model based on the feedback for one ofthe multi-leaf collimator, the gantry, the couch, and the jaws,calculating a delivered dose amount based on the mathematical model andtreatment plan information, calculating a deviation in dose between theradiation amount specified in the treatment plan and the delivered doseamount, and determining whether the deviation in dose is within adosimetric tolerance for the one of the multi-leaf collimator, thegantry, the couch, and the jaws.

In another embodiment, the invention provides a method of determiningwhether a component of a radiation therapy system deviated fromspecified operation. The method comprises generating a treatment planfor a patient, the treatment plan specifying a radiation amount to bedelivered to the patient, delivering radiation to the patient accordingto the treatment plan, obtaining feedback during the delivery ofradiation, the feedback related to one of a position, a velocity, and anacceleration for one of a multi-leaf collimator, a gantry, a couch, anda jaws, calculating a delivered dose amount based on the feedback,calculating a deviation in dose between the radiation amount specifiedin the treatment plan and the delivered dose amount, and adjusting oneof the multi-leaf collimator, the gantry, the couch, and the jaws tominimize the deviation in dose.

Other aspects of the invention will become apparent by consideration ofthe detailed description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of a radiation therapy treatment system.

FIG. 2 is a perspective view of a multi-leaf collimator that can be usedin the radiation therapy treatment system illustrated in FIG. 1.

FIG. 3 is a schematic illustration of the radiation therapy treatmentsystem of FIG. 1.

FIG. 4 is a schematic diagram of a software program used in theradiation therapy treatment system chart of a method of evaluating thedelivery of a treatment plan according to one embodiment of the presentinvention.

FIG. 5 is a flow chart of a method of verifying system-level qualityassurance according to one embodiment of the present invention.

FIG. 6 is a flow chart of a method of verifying system-level qualityassurance according to one embodiment of the present invention.

DETAILED DESCRIPTION

Before any embodiments of the invention are explained in detail, it isto be understood that the invention is not limited in its application tothe details of construction and the arrangement of components set forthin the following description or illustrated in the following drawings.The invention is capable of other embodiments and of being practiced orof being carried out in various ways. Also, it is to be understood thatthe phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including,” “comprising,” or “having” and variations thereof herein ismeant to encompass the items listed thereafter and equivalents thereofas well as additional items. Unless specified or limited otherwise, theterms “mounted,” “connected,” “supported,” and “coupled” and variationsthereof are used broadly and encompass both direct and indirectmountings, connections, supports, and couplings.

Although directional references, such as upper, lower, downward, upward,rearward, bottom, front, rear, etc., may be made herein in describingthe drawings, these references are made relative to the drawings (asnormally viewed) for convenience. These directions are not intended tobe taken literally or limit the present invention in any form. Inaddition, terms such as “first,” “second”, and “third” are used hereinfor purposes of description and are not intended to indicate or implyrelative importance or significance.

In addition, it should be understood that embodiments of the inventioninclude hardware, software, and electronic components or modules that,for purposes of discussion, may be illustrated and described as if themajority of the components were implemented solely in hardware. However,one of ordinary skill in the art, and based on a reading of thisdetailed description, would recognize that, in at least one embodiment,the electronic based aspects of the invention may be implemented insoftware. As such, it should be noted that a plurality of hardware andsoftware based devices, as well as a plurality of different structuralcomponents may be utilized to implement the invention. Furthermore, andas described in subsequent paragraphs, the specific mechanicalconfigurations illustrated in the drawings are intended to exemplifyembodiments of the invention and that other alternative mechanicalconfigurations are possible.

FIG. 1 illustrates a radiation therapy treatment system 10 that canprovide radiation therapy to a patient 14. The radiation therapytreatment can include photon-based radiation therapy, brachytherapy,electron beam therapy, proton, neutron, or particle therapy, or othertypes of treatment therapy. The radiation therapy treatment system 10includes a gantry 18. The gantry 18 can support a radiation module 22,which can include a radiation source 24 and a linear accelerator 26(a.k.a. “a linac”) operable to generate a beam 30 of radiation. Thoughthe gantry 18 shown in the drawings is a ring gantry, i.e., it extendsthrough a full 360° arc to create a complete ring or circle, other typesof mounting arrangements may also be employed. For example, a C-type,partial ring gantry, or robotic arm could be used. Any other frameworkcapable of positioning the radiation module 22 at various rotationaland/or axial positions relative to the patient 14 may also be employed.In addition, the radiation source 24 may travel in path that does notfollow the shape of the gantry 18. For example, the radiation source 24may travel in a non-circular path even though the illustrated gantry 18is generally circular-shaped.

The radiation module 22 can also include a modulation device 34 operableto modify or modulate the radiation beam 30. The modulation device 34provides the modulation of the radiation beam 30 and directs theradiation beam 30 toward the patient 14. Specifically, the radiationbeam 30 is directed toward a portion 38 of the patient. Broadlyspeaking, a portion 38 may include the entire body, but is generallysmaller than the entire body and can be defined by a two-dimensionalarea and/or a three-dimensional volume. A portion or area 38 desired toreceive the radiation, which may be referred to as a target or targetregion, is an example of a region of interest. Another type of region ofinterest is a region at risk. If a portion 38 includes a region at risk,the radiation beam is preferably diverted from the region at risk. Suchmodulation is sometimes referred to as intensity modulated radiationtherapy (“IMRT”).

The modulation device 34 can include a collimation device 42 asillustrated in FIG. 2. The collimation device 42 includes a set of jaws46 that define and adjust the size of an aperture 50 through which theradiation beam 30 may pass. The jaws 46 include an upper jaw 54 and alower jaw 58. The upper jaw 54 and the lower jaw 58 are moveable toadjust the size of the aperture 50. The position of the jaws 46regulates the shape of the beam 30 that is delivered to the patient 14.

In one embodiment, and illustrated in FIG. 2, the modulation device 34can comprise a multi-leaf collimator 62 (a.k.a. “MLC”), which includes aplurality of interlaced leaves 66 operable to move from position toposition, to provide intensity modulation. It is also noted that theleaves 66 can be moved to a position anywhere between a minimally andmaximally-open position. The plurality of interlaced leaves 66 modulatethe strength, size, and shape of the radiation beam 30 before theradiation beam 30 reaches the portion 38 on the patient 14. Each of theleaves 66 is independently controlled by an actuator 70, such as a motoror an air valve so that the leaf 66 can open and close quickly to permitor block the passage of radiation. The actuators 70 can be controlled bya computer 74 and/or controller.

The radiation therapy treatment system 10 can also include a detector78, e.g., a kilovoltage or a megavoltage detector, operable to receivethe radiation beam 30 as illustrated in FIG. 1. The linear accelerator26 and the detector 78 can also operate as a computed tomography (CT)system to generate CT images of the patient 14. The linear accelerator26 emits the radiation beam 30 toward the portion 38 in the patient 14.The portion 38 absorbs some of the radiation. The detector 78 detects ormeasures the amount of radiation absorbed by the portion 38. Thedetector 78 collects the absorption data from different angles as thelinear accelerator 26 rotates around and emits radiation toward thepatient 14. The collected absorption data is transmitted to the computer74 to process the absorption data and to generate images of thepatient's body tissues and organs. The images can also illustrate bone,soft tissues, and blood vessels.

The radiation therapy treatment system 10 can also include a patientsupport, such as a couch 82, operable to support at least a portion ofthe patient 14 during treatment. While the illustrated couch 82 isdesigned to support the entire body of the patient 14, in otherembodiments of the invention, the patient support need not support theentire body, but rather can be designed to support only a portion of thepatient 14 during treatment. The couch 82 moves into and out of thefield of radiation along an axis 84 (i.e., Y axis). The couch 82 is alsocapable of moving along the X and Z axes as illustrated in FIG. 1.

The computer 74, illustrated in FIGS. 2 and 3, includes an operatingsystem for running various software programs (e.g., a computer readablemedium capable of generating instructions) and/or a communicationsapplication. In particular, the computer 74 can include a softwareprogram(s) 90 that operates to communicate with the radiation therapytreatment system 10. The computer 74 can include any suitableinput/output device adapted to be accessed by medical personnel. Thecomputer 74 can include typical hardware such as a processor, I/Ointerfaces, and storage devices or memory. The computer 74 can alsoinclude input devices such as a keyboard and a mouse. The computer 74can further include standard output devices, such as a monitor. Inaddition, the computer 74 can include peripherals, such as a printer anda scanner.

The computer 74 can be networked with other computers 74 and radiationtherapy treatment systems 10. The other computers 74 may includeadditional and/or different computer programs and software and are notrequired to be identical to the computer 74, described herein. Thecomputers 74 and radiation therapy treatment system 10 can communicatewith a network 94. The computers 74 and radiation therapy treatmentsystems 10 can also communicate with a database(s) 98 and a server(s)102. It is noted that the software program(s) 90 could also reside onthe server(s) 102.

The network 94 can be built according to any networking technology ortopology or combinations of technologies and topologies and can includemultiple sub-networks. Connections between the computers and systemsshown in FIG. 3 can be made through local area networks (“LANs”), widearea networks (“WANs”), public switched telephone networks (“PSTNs”),wireless networks, Intranets, the Internet, or any other suitablenetworks. In a hospital or medical care facility, communication betweenthe computers and systems shown in FIG. 3 can be made through the HealthLevel Seven (“HL7”) protocol or other protocols with any version and/orother required protocol. HL7 is a standard protocol which specifies theimplementation of interfaces between two computer applications (senderand receiver) from different vendors for electronic data exchange inhealth care environments. HL7 can allow health care institutions toexchange key sets of data from different application systems.Specifically, HL7 can define the data to be exchanged, the timing of theinterchange, and the communication of errors to the application. Theformats are generally generic in nature and can be configured to meetthe needs of the applications involved.

Communication between the computers and systems shown in FIG. 3 can alsooccur through the Digital Imaging and Communications in Medicine (DICOM)protocol with any version and/or other required protocol. DICOM is aninternational communications standard developed by NEMA that defines theformat used to transfer medical image-related data between differentpieces of medical equipment. DICOM RT refers to the standards that arespecific to radiation therapy data.

The two-way arrows in FIG. 3 generally represent two-way communicationand information transfer between the network 94 and any one of thecomputers 74 and the systems 10 shown in FIG. 3. However, for somemedical and computerized equipment, only one-way communication andinformation transfer may be necessary.

The software program 90 (illustrated in block diagram form in FIG. 4)includes a plurality of modules or applications that communicate withone another to perform one or more functions of the radiation therapytreatment process. The software program 90 can transmit instructions toor otherwise communicate with various components of the radiationtherapy treatment system 10 and to components and/or systems external tothe radiation therapy treatment system 10. The software program 90 alsogenerates a user interface that is presented to the user on a display,screen, or other suitable computer peripheral or other handheld devicein communication with the network 94. The user interface allows the userto input data into various defined fields to add data, remove data,and/or to change the data. The user interface also allows the user tointeract with the software program 90 to select data in any one or morethan one of the fields, copy the data, import the data, export the data,generate reports, select certain applications to run, rerun any one ormore of the accessible applications, and perform other suitablefunctions.

The software program 90 includes an image module 104 operable to acquireor receive images of at least a portion of the patient 14. The imagemodule 104 can instruct the on-board image device, such as a CT imagingdevice to acquire images of the patient 14 before treatment commences,during treatment, and after treatment according to desired protocols.For CT images, the data comprising the patient images are composed ofimage elements, which represent image elements stored as data in theradiation therapy treatment system. These image elements may be any dataconstruct used to represent image data, including two-dimensional pixelsor three-dimensional voxels.

In one aspect, the image module 104 acquires an image of the patient 14while the patient 14 is substantially in a treatment position. Otheroff-line imaging devices or systems may be used to acquire pre-treatmentimages of the patient 14, such as non-quantitative CT, MRI, PET, SPECT,ultrasound, transmission imaging, fluoroscopy, RF-based localization,and the like. The acquired images can be used for registration/alignmentof the patient 14 with respect to the gantry or other point and/or todetermine or predict a radiation dose to be delivered to the patient 14.The acquired images also can be used to generate a deformation map toidentify the differences between one or more of the planning images andone or more of the pre-treatment (e.g., a daily image),during-treatment, or after-treatment images. The acquired images alsocan be used to determine a radiation dose that the patient 14 receivedduring the prior treatments. The image module 104 also is operable toacquire images of at least a portion of the patient 14 while the patientis receiving treatment to determine a radiation dose that the patient 14is receiving in real-time.

The software program 90 includes a treatment plan module 106 operable togenerate a treatment plan, which defines a treatment regimen for thepatient 14 based on data input to the system 10 by medical personnel.The data can include one or more images (e.g., planning images and/orpre-treatment images) of at least a portion of the patient 14. Theseimages may be received from the image module 104 or other imagingacquisition device. The data can also include one or more contoursreceived from or generated by a contour module 108. During the treatmentplanning process, medical personnel utilize one or more of the images togenerate one or more contours on the one or more images to identify oneor more treatment regions or avoidance regions of the portion 38. Thecontour process can include using geometric shapes, includingthree-dimensional shapes to define the boundaries of the treatmentregion of the portion 38 that will receive radiation and/or theavoidance region of the portion 38 that will receive minimal or noradiation. The medical personnel can use a plurality of predefinedgeometric shapes to define the treatment region(s) and/or the avoidanceregion(s). The plurality of shapes can be used in a piecewise fashion todefine irregular boundaries. The treatment plan module 106 can separatethe treatment into a plurality of fractions and can determine the amountof radiation dose for each fraction or treatment (including the amountof radiation dose for the treatment region(s) and the avoidanceregion(s)) based at least on the prescription input by medicalpersonnel.

The software program 90 can also include a contour module 108 operableto generate one or more contours on a two-dimensional orthree-dimensional image. Medical personnel can manually define a contouraround a target 38 on one of the patient images. The contour module 108receives input from a user that defines a margin limit to maintain fromother contours or objects. The contour module 108 can include a libraryof shapes (e.g., rectangle, ellipse, circle, semi-circle, half-moon,square, etc.) from which a user can select to use as a particularcontour. The user also can select from a free-hand option. The contourmodule 108 allows a user to drag a mouse (a first mouse draggingmovement or swoop) or other suitable computer peripheral (e.g., stylus,touchscreen, etc.) to create the shape on a transverse view of an imageset. An image set can include a plurality of images representing variousviews such as a transverse view, a coronal view, and a sagittal view.The contour module 108 can automatically adjust the contour shape tomaintain the user-specified margins, in three dimensions, and can thendisplay the resulting shape. The center point of the shape can be usedas an anchor point. The contour module 108 also allows the user to dragthe mouse a second time (a second consecutive mouse dragging movement orswoop) onto a coronal or sagittal view of the image set to create an“anchor path.” The same basic contour shape is copied or translated ontothe corresponding transverse views, and can be automatically adjusted toaccommodate the user-specified margins on each view independently. Theshape is moved on each view so that the new shape's anchor point iscentered on a point corresponding to the anchor path in the coronal andsagittal views. The contour module 108 allows the user to makeadjustments to the shapes on each slice. The user may also makeadjustments to the limits they specified and the contour module 108updates the shapes accordingly. Additionally, the user can adjust theanchor path to move individual slice contours accordingly. The contourmodule 108 provides an option for the user to accept the contour set,and if accepted, the shapes are converted into normal contours forediting.

During the course of treatment, the patient typically receives aplurality of fractions of radiation (i.e., the treatment plan specifiesthe number of fractions to irradiate the tumor). For each fraction, thepatient is registered or aligned with respect to the radiation deliverydevice. After the patient is registered, a daily pre-treatment image(e.g., a 3D or volumetric image) is acquired while the patient remainsin substantially a treatment position. The pre-treatment image can becompared to previously acquired images of the patient to identify anychanges in the target 38 or other structures over the course oftreatment. The changes in the target 38 or other structures is referredto as deformation. Deformation may require that the original treatmentplan be modified to account for the deformation. Instead of having torecontour the target 38 or the other structures, the contour module 114can automatically apply and conform the preexisting contours to takeinto account the deformation. To do this, a deformation algorithm(discussed below) identifies the changes to the target 38 or otherstructures. These identified changes are input to the contour module114, which then modifies the contours based on those changes.

The software program 90 can also include a deformation module 110operable to deform an image(s) while improving the anatomicalsignificance of the results. The deformation of the image(s) can be usedto generate a deformation map to identify the differences between one ormore of the planning images and one or more of the daily images.

The deformed image(s) also can be used for registration of the patient14 and/or to determine or predict a radiation dose to be delivered tothe patient 14. The deformed image(s) also can be used to determine aradiation dose that the patient 14 received during the prior treatmentsor fractions. The image module 104 also is operable to acquire one orimages of at least a portion of the patient 14 while the patient isreceiving radiation treatment that can be deformed to determine aradiation dose that the patient 14 is receiving in real-time.

The software program 90 also includes a patient positioning module 112operable to position and align the patient 14 with respect to theisocenter of the gantry 18 for a particular treatment fraction. Whilethe patient is on the couch 82, the patient positioning module 112acquires an image of the patient 14 and compares the current position ofthe patient 14 to the position of the patient in a reference image. Thereference image can be a planning image, any pre-treatment image, or acombination of a planning image and a pre-treatment image. If thepatient's position needs to be adjusted, the patient positioning module112 provides instructions to the drive system 86 to move the couch 82 orthe patient 14 can be manually moved to the new position. In oneconstruction, the patient positioning module 112 can receive data fromlasers positioned in the treatment room to provide patient position datawith respect to the isocenter of the gantry 18. Based on the data fromthe lasers, the patient positioning module 112 provides instructions tothe drive system 86, which moves the couch 82 to achieve properalignment of the patient 14 with respect to the gantry 18. It is notedthat devices and systems, other than lasers, can be used to provide datato the patient positioning module 112 to assist in the alignmentprocess.

The patient positioning module 112 also is operable to detect and/ormonitor patient motion during treatment. The patient positioning module112 may communicate with and/or incorporate a motion detection system114, such as x-ray, in-room CT, laser positioning devices, camerasystems, spirometers, ultrasound, tensile measurements, chest bands, andthe like. The patient motion can be irregular or unexpected, and doesnot need to follow a smooth or reproducible path.

The software program 90 also includes a treatment delivery module 116operable to instruct the radiation therapy treatment system 10 todeliver the treatment plan to the patient 14 according to the treatmentplan. The treatment delivery module 116 can generate and transmitinstructions to the gantry 18, the linear accelerator 26, the modulationdevice 34, and the drive system 86 to deliver radiation to the patient14. The instructions coordinate the necessary movements of the gantry18, the modulation device 34, and the drive system 86 to deliver theradiation beam 30 to the proper target in the proper amount as specifiedin the treatment plan.

The treatment delivery module 116 also calculates the appropriatepattern, position, and intensity of the radiation beam 30 to bedelivered, to match the prescription as specified by the treatment plan.The pattern of the radiation beam 30 is generated by the modulationdevice 34, and more particularly by movement of the plurality of leavesin the multi-leaf collimator. The treatment delivery module 116 canutilize canonical, predetermined or template leaf patterns to generatethe appropriate pattern for the radiation beam 30 based on the treatmentparameters. The treatment delivery module 116 can also include a libraryof patterns for typical cases that can be accessed in which to comparethe present patient data to determine the pattern for the radiation beam30.

The software program 90 also includes a feedback module 118 operable toreceive data from the radiation therapy treatment system 10 during apatient treatment. The feedback module 118 can receive data from theradiation therapy treatment device and can include information relatedto patient transmission data, ion chamber data, MLC data, systemtemperatures, component speeds and/or positions, flow rates, etc. Thefeedback module 118 can also receive data related to the treatmentparameters, amount of radiation dose the patient received, image dataacquired during the treatment, and patient movement. In addition, thefeedback module 118 can receive input data from a user and/or othersources. The feedback module 118 acquires and stores the data untilneeded for further processing.

The feedback module 118 can obtain feedback from encoders and sensorspositioned on various subsystems and/or components (such as the MLC,gantry, couch, and jaws) of the radiation therapy treatment system 10.The encoders and sensors can provide feedback by detecting ordetermining position, velocity, and/or acceleration data. For each ofthese subsystems, a mathematical model is applied to the feedback (withor without additional data) which allows the feedback module 118 toderive or determine a dosimetric error from this feedback. Withaggregate “real-time” data from all such subsystems combined withtreatment plan information, such as patient CT data, dose output fromdose monitor chambers, and other treatment plan parameters, the feedbackmodule 118 can compute a calculated delivered dose as well as delivereddose error. The delivered dose error can be mathematically simplifiedfor low cost implementation.

There are three potential applications for the use of calculateddelivered dose and delivered dose error: (1) dosimetric tolerancing, (2)system dosimetric servo, and (3) delivery verification using real-timefeedback.

Dosimetric Tolerancing

Most control systems use a predefined fixed tolerance to determine whenthe system is performing according to specification. This may be acalibrated value or hard-coded into the system. For example, the currentHi-Art® treatment couch uses a 1 mm tolerance defined in the softwareprogram to determine when it is within specification during treatment.

A dosimetric tolerance uses a model of expected dose in conjunction withreal-time encoder feedback to compute a dosimetric error. A single dosetolerance calculation system may take real-time feedback from allmodulated subsystems in the machine and derive a calculated delivereddose and delivered dose error based on treatment plan information andmodel of how each subsystem affects overall treatment dose. Thiscalculated dose can provide a better understanding of the quality of thepatient treatment and be used to determine that the system is operatingwithin dosimetric tolerance.

System Dosimetric Servo

A servo system utilizes a feedback signal such as an encoder todetermine its position, computes an error value, then uses this toadjust motor torque or speed to remove the error. This may also bedescribed as a closed loop system or PID.

Each modulated subsystem in the Hi-Art® treatment system (MLC, gantry,couch, jaws) utilizes some form of servo control to maintain correctposition, velocity, and acceleration during treatment. The positionfeedback is primarily a combination of incremental and absolute encoderfeedback. While a given subsystem may exhibit a certain amount of error,there is no understanding of the impact of this error to the overalldose delivered to the patient.

The concept of system dosimetric servo involves using a real-timecalculated delivered dose as defined above to determine dosimetric erroras feedback. A dosimetric servo program uses this dose error and amathematical model of dose (PID) to make adjustments to subsystems tocorrect the dose and minimize the dose error.

Delivery Verification Using Real-Time Feedback

With a model of delivered dose derived from each modulated subsystem inthe Hi-Art® system as described above, verification of delivered dosemay be performed in real-time during treatment delivery. Using treatmentplan parameters such as a CT image in conjunction with real-timefeedback from modulated subsystems (MLC, gantry, couch, jaws), delivereddose can be calculated at any point in time and compared to theprescribed dose. Accumulated delivered dose may be calculated duringtreatment delivery and saved to disk and/or memory for later deliveryverification or plan adaptation.

The software program 90 also includes an analysis module 122 operable toanalyze the data from the feedback module 118 to determine whetherdelivery of the treatment plan occurred as intended and to validate thatthe planned delivery is reasonable based on the newly-acquired data. Theanalysis module 122 can also determine, based on the received dataand/or additional inputted data, whether a problem has occurred duringdelivery of the treatment plan. For example, the analysis module 122 candetermine if the problem is related to an error of the radiation therapytreatment device 10, an anatomical error, such as patient movement,and/or a clinical error, such as a data input error. The analysis module122 can detect errors in the radiation therapy treatment device 10related to the couch 82, the device output, the gantry 18, themulti-leaf collimator 62, the patient setup, and timing errors betweenthe components of the radiation therapy treatment device 10. Forexample, the analysis module 122 can determine if a couch replacementwas performed during planning, if fixation devices were properly usedand accounted for during planning, and if position and speed are correctduring treatment delivery. The analysis module 122 can determine whetherchanges or variations occurred in the output parameters of the radiationtherapy treatment device 10. With respect to the gantry 18, the analysismodule 122 can determine if there are errors in the speed andpositioning of the gantry 18. The analysis module 122 can receive datato determine if the multi-leaf collimator 62 is operating properly. Forexample, the analysis module 122 can determine if the leaves 66 move atthe correct times, if any leaves 66 are stuck in place, if leaf timingis properly calibrated, and whether the leaf modulation pattern iscorrect for any given treatment plan. The analysis module 122 also canvalidate patient setup, orientation, and position for any giventreatment plan. The analysis module 122 also can validate that thetiming between the gantry 18, the couch 62, the linear accelerator 26,and the leaves 66 are correct.

The analysis module 122 can also utilize deformable registration data toensure that the patient 14 is receiving the correct radiation doseacross multiple fractions. When analyzing the doses, it is useful toaccumulate the dose across multiple treatment fractions to determine ifany errors are being exacerbated or if they are mitigating each other.Registration is a method for determining the correlation betweenlocations of a patient's anatomy or physiology across multiple images.Deformable registration is a method of determining the correlationbetween locations of a patient's anatomy or physiology to account fornon-rigid changes in anatomy between the images, phases, or times. Theradiation dose delivered to the patient 14 is recalculated based uponon-line images and feedback from the radiation therapy treatment device10 to ensure that the correct dose has been or is being delivered to thepatient 14.

The analysis module 122 also can utilize data related todeformation-based contouring of images for quality assurance purposes.Deformable registration techniques can be used to generate automatic orsemi-automatic contours for new images. Generally, a contour set hasbeen defined for planning or other baseline patient images, but with newimages, a contour set is not usually readily available. Rather thanrequire an operator to manually contour the image, it can be both fasterand more consistent to perform a deformable image registration, and thenuse the deformation results as the basis for modifying the originalcontour set to reflect the new patient anatomy. A similar family oftemplate-based contouring algorithms has been developed to generatecontours for newly available images, based upon previously availablesets of images and contours. These template-based algorithms mightcontour a new patient image based upon a previous patient image andcontour, or potentially based upon a canonical or atlas patient imageand contour. This can be performed for adaptive therapy as a means toaccumulate doses in daily images, each with automatic daily contours.Moreover, whereas previously these algorithms were used in the contextof generating new contours based upon canonical or atlas images, it is anew aspect of this invention to apply these techniques to the particularwealth of image data and types of images that arise during image-guidedradiotherapy. Specifically, this includes deformation and template-basedcontouring of multiple images of the same patient in which contour setsmight only exist for one of the images. These multiple images of thepatient may arise from use of an on-line or in-room patient imagingsystem, with images potentially taken on different days, or these imagesmight derive from a “4D” imaging system such as a CT scanner, in whicheach image represents a phase of motion, such as a breathing phase. Itshould also be noted that the on-line or in-room imaging system might bethe same, a similar, or a different modality from the reference image.For example, the reference image might be a CT image, whereas theon-line image could be CT, cone-beam CT, megavoltage CT, MRI,ultrasound, or a different modality. By porting these contouringtechniques to the applications of quality assurance and adaptivetherapy, it is possible to both save a considerable amount of time fromthe contouring of images, and this method can also improve theconsistency of contours across multiple images of the same patient(taken at different times or representing different phases). It is knownthat manual contours can suffer from irreproducibility, whereasautomatically generated contours can potentially be more consistent inapplying the principles of an initial contour to the generation ofsubsequent contours.

Another benefit of the contouring process using deformable registrationtechniques is that the contours generated can provide a validation ofthe deformation process. If the generated contours closely reflectcontours that one would manually draw, then it is a good indication thatthe deformation process is reasonable; whereas if the automatic contoursare less relevant, it indicates to the user that perhaps the deformationis inappropriate, but also provides the user an opportunity to verifythe manual contours to check for mistakes or inconsistencies. Anotheraspect of this method is that the deformation-based contours can be usedas a rough-draft of the contours for the adaptive process, and manuallyedited to reflect the desired contours for the on-line images. Whendoing this, the deformation process can then be re-run, constraining thedeformation map to match the initial contours to the manually-editedautomatic contours, and this helps direct consistent results through therest of the image.

The analysis module 122 also is operable to utilize deformation maps toperform dose calculations on various images for quality assurancepurposes. A deformation map can be utilized to relate a plurality ofimages where one image is a planning image that is useful for dosecalculation, and another image, such as an on-line image, hasqualitative value but less direct utility for dose calculation. Thisrelation could then be used to “remap” the more quantitative image tothe qualitative shape of the on-line or less quantitative image. Theresulting remapped image would be more appropriate than either of theother two images for dose calculation or quantitative applications as itwould have the quantitative benefits of the first image, but with theupdated anatomical information as contained in the second image. Thiscould be useful in a variety of cases, such as where the first image(e.g., a planning image) is a CT and where the additional image lacksquantitative image values (e.g., MRI, PET, SPECT, ultrasound, ornon-quantitative CT, etc. images). A similar application of this methodwould be to correct for geometrical distortion, imperfections, and/orincompleteness in lieu of, or in addition to, quantitative limitations.For example, a current MRI image that well represents anatomy butincludes geometric distortion might be remapped to a CT image that isnot distorted. Or multiple images could be used to simultaneouslycorrect for both distortion while representing anatomical changes.

As noted above, it is important to be able to recalculate dose onpatient images acquired after the planning image. Given these doses, itis also useful to accumulate these doses for multiple deliveredfractions. These doses can be added based upon the location of the dosesin physical space, but a better method is to incorporate deformationmethods into the process so as to add doses based upon the structuresthat received the dose, even if the structures have changed location.However, it is possible to build upon this technology to perform noveltypes of adaptive therapy.

In the context of recalculating doses, there are several other aspectsof this invention to improve or facilitate this process. For example,after recording any daily registrations applied to the patient,potentially based upon image-guidance, these same registrations canoptionally be applied to the patient images when recalculating dose.This can be performed automatically or semi-automatically. Alternately,the dose could be recalculated with a different registration. Thebenefit is that by automatically using the recorded registrations, theprocess of recalculating the doses that were delivered is simplified andstreamlined. Moreover, by having the ability to recalculate doses fordifferent registrations, one can experiment to determine if otherpatient alignment protocols might have been more or less effective. Andby not using the recorded registration, one can determine how thetreatment would have been affected in the absence of image guidance.

The dose recalculation process also can be enhanced by the padding ofincomplete images. This is because a limited-size image, whether limitedin the axial plane and/or in the superior/inferior direction, candegrade the accuracy of dose calculations. A method to overcome this isto pad the limited-size image with other image data, such as from theplanning image. This padding method can work for both axially orsuperior/inferior limited data. In addition, another method for paddingsuperior/inferior data is to repeat the end slices of the incompleteimage as necessary until the data is sufficiently large for improveddose calculation.

Additional aspects of dose recalculation entail the calculation of doseto account for true 4D motion. Previous teachings describe methods forgenerating “4D CT” images, which are a time-based series of images or acollection of 3D image volumes that each represents a “phase” of amotion pattern, such as breathing. These images have been used forcontouring, and even for generating treatment plans that anticipate acertain cycle of “phases”. However, patient breathing can often deviatefrom the ideally reproducible pattern indicated by a “4D CT” image set.The invention provides a method to recalculate dose more accurately onone of these volumes. This entails using a motion detection system 114to monitor the patient's motion during treatment. This motion can beirregular or unexpected, and need not follow a smooth or reproducibletrajectory. And the motion can be detected with any of a number ofmonitoring systems including x-ray, in-room CT, laser positioningdevices, camera systems, spirometers, ultrasound, tensile measurements,or the like. Given these measurements, the dose can be recalculated forthe patient's actual delivery by using the measured data to indicate thephase the patient was in at any given time, and recalculating the dosefor each time in the phase of the 4D CT image best matching thepatient's instantaneous position. This can also be performed using CTimages collected simultaneously with patient treatment. In this lattercase, phase identification might not be necessary. In one embodiment,deformation techniques would be used to accumulate doses between thedifferent phases or images. In addition, the generation of updated 4D CTimages before or during treatment could be used in conjunction with thismethod, as could other types of 4D images that are not strictly CT, suchas 4D PET or 4D MRI, although these would typically require somemodification to use these images quantitatively.

One application of this technology is to correct for poor treatments,such as what could result from poor planning, or poor delivery of aplan. The analysis module 122 can analyze the net dose delivered, andgenerate corrective plans to deliver the net desired dose or a dosechosen to match the intended biological effect. The original treatmentswould not need to be limited to photon-based radiation therapy, butcould be any form of treatment including brachytherapy, electron beamtherapy, proton, neutron, or particle therapy, or other types oftreatments.

Another aspect of this invention is that the concept of adaptive therapycan be applied not only based upon the doses received alone, but also onpredicted trends in the patient's treatment, clinical results, machinechanges, and/or biological markers. For example, if a trend is detectedin that a tumor is shrinking, or that a normal tissue structure isgradually migrating, the adaptive planning process could not onlyaccount for the current status of the patient and the doses delivered todate, but could also generate plans that reflect anticipated furtherchanges in anatomy. Similarly, when analyzing cumulative doseinformation during the course of a treatment, the clinician can alsoconsider the level of clinical effects and side-effects that the patientis experiencing, either based upon clinical findings or availablebiological markers or tests. If few side effects are felt, a moreaggressive adaptive therapy treatment might be pursued, whereas if morecomplications are detected, the therapy might be modified to betteravoid the affected region. Furthermore, plans can be adapted tocompensate for detected changes in the machine, such as variations inoutput, energy, or calibration.

A variation of this theme is to perform a radiobiopsy. Early in atreatment, or before radiation treatment fully begins, the patient mayreceive a treatment fraction with a high radiation dose to a localizedregion, or potentially a dose only to a localized region. The effects onthis region can be monitored to determine the nature of that region,such as whether it is tumorous, and what type. An appropriate course oftreatment can be determined based upon these results, and the dosealready delivered can be incorporated into the planning process.

FIG. 5 illustrates a flow chart of a method of verifying system-levelquality assurance. Medical personnel acquire (at 200) an image of thepatient and generate (at 204) a treatment plan for the patient 14 basedon patient data, images, or other information. When the patient 14 isready for a treatment, medical personnel position (at 208) the patient14 on the couch 82 with the assistance of the patient positioning module112 prior to delivery of treatment. Medical personnel initiate (at 212)acquisition of an on-line image of the patient 14 to assist in thepositioning or alignment process. Additional positioning adjustments canbe made as necessary. After the patient 14 is properly positioned, theuser initiates (at 216) the treatment according to the treatment planwith the assistance of the treatment delivery module 116. Duringdelivery of the treatment plan, the feedback module 118 acquires (at220) data related to the radiation therapy treatment device 10 andpatient parameters. During and/or after treatment, the analysis module122 calculates (at 224) a radiation dose received by the patient 14 anddetermines (at 228) whether the delivery of the treatment plan occurredas intended.

FIG. 6 illustrates a flow chart of a method of verifying system-levelquality assurance. Medical personnel acquire (at 250) an image of thepatient and generate (at 254) a treatment plan for the patient 14 basedon patient data, images, or other information. When the patient 14 isready for a treatment, medical personnel position (at 258) the patient14 on the couch 82 with the assistance of the patient positioning module112 prior to delivery of treatment. Medical personnel initiate (at 262)acquisition of an on-line image of the patient 14 to assist in thepositioning process. Additional positioning adjustments can be made asnecessary. Medical personnel initiate (at 266) generation of adeformation map between one of the images in the treatment plan and theon-line image. After the patient 14 is properly positioned, the userinitiates (at 270) the treatment according to the treatment plan withthe assistance of the treatment delivery module 116. During delivery ofthe treatment plan, the feedback module 118 acquires (at 274) datarelated to the radiation therapy treatment device 10 and patientparameters. During and/or after treatment, the analysis module 122calculates (at 278) a radiation dose received by the patient 14 anddetermines (at 282) whether the delivery of the treatment plan occurredas intended.

Various features and advantages of the invention are set forth in thefollowing claims.

1. A method of determining whether a component of a radiation therapy system is operating within a dosimetric tolerance, the method comprising: generating a treatment plan for a patient, the treatment plan specifying a radiation amount to be delivered to the patient; delivering radiation to the patient according to the treatment plan; obtaining feedback during the delivery of radiation, the feedback related to one of a position, a velocity, and an acceleration for one of a multi-leaf collimator, a gantry, a couch, and a jaws; generating a mathematical model based on the feedback for one of the multi-leaf collimator, the gantry, the couch, and the jaws; calculating a delivered dose amount based on the mathematical model and treatment plan information; calculating a deviation in dose between the radiation amount specified in the treatment plan and the delivered dose amount; and determining whether the deviation in dose is within a dosimetric tolerance for the one of the multi-leaf collimator, the gantry, the couch, and the jaws.
 2. A method of determining whether a component of a radiation therapy system deviated from specified operation, the method comprising: generating a treatment plan for a patient, the treatment plan specifying a radiation amount to be delivered to the patient; delivering radiation to the patient according to the treatment plan; obtaining feedback during the delivery of radiation, the feedback related to one of a position, a velocity, and an acceleration for one of a multi-leaf collimator, a gantry, a couch, and a jaws; calculating a delivered dose amount based on the feedback; calculating a deviation in dose between the radiation amount specified in the treatment plan and the delivered dose amount; and adjusting one of the multi-leaf collimator, the gantry, the couch, and the jaws to minimize the deviation in dose. 